The emerging role of Deep learning in cytology.

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Abstract

Deep learning (DL) is a component or subset of artificial intelligence. DL has contributed significant change in the feature extraction and image classification. The various algorithmic models are used in DL such as a convolutional neural network (CNN), recurrent neural network, restricted Boltzman machine, deep belief network and autoencoders. Out of which CNN is the commonly used algorithm in the field of pathology for the feature extraction and building neural network model. DL system may be useful for tumour diagnosis, classification of the tumour and grading of the tumour in cytology. In this brief review, the basic concept of the DL and CNN has been described. Besides, the application, prospects and challenges of the DL in the cytology are also discussed.
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